High Level Image Processingยถ
- Class:
- Alias:
highlevel_pipeline
The HighLevelPipeline applies corrections to an overlapping group of images
and is setup to process only imaging observations.
This pipeline is used to determine a common background, skymatch, detect pixels the are
not consistent with the other datasets, outlier_detection, and resample the image to a
single undistorted image, resample.
The list of steps applied by the HighLevelPipeline pipeline is shown in the
table below.
Step |
WFI-Image |
WFI-Prism |
WFI-Grism |
|---|---|---|---|
โ |
๐ |
๐ |
|
โ |
๐ |
๐ |
|
โ |
๐ |
๐ |
Argumentsยถ
The highlevel pipeline has no optional arguments:
You can see the options for strun using:
strun โhelp roman_hlp
and this will list all the strun options all well as the step options for the roman_hlp.
Inputsยถ
2D image dataยถ
- Data model:
WfiImage- File suffix:
_cal
The input to the HighLevelPipeline is a group of calibrated exposures,
e.g. โr0008308002010007027_06311_0019_WFI01_cal.asdfโ, which contains the
calibrated data for the the exposures. The most convenient way to pass the list of
exposures to be processed with the high level pipeline is to use an association.
Instructions on how to create an input association an be found at asn_from_list.
Outputsยถ
2D Image modelยถ
- Data model:
WfiMosaic- File suffix:
_i2d
Result of applying all the high level pipeline steps up through the resample step is to produce data background corrected and cleaned of outliers and resampled to a distortion free grid. This is 2D image data, with additional attributes for the mosaicing information.